中文簡(jiǎn)介

《國(guó)際數(shù)據(jù)倉(cāng)庫(kù)與挖掘雜志》（IJDWM）發(fā)布了數(shù)據(jù)管理和分析領(lǐng)域的最新國(guó)際研究成果。IJDWM為最先進(jìn)的開(kāi)發(fā)和研究提供了一個(gè)論壇，以及當(dāng)前專注于數(shù)據(jù)倉(cāng)庫(kù)和數(shù)據(jù)挖掘領(lǐng)域集成的創(chuàng)新活動(dòng)。強(qiáng)調(diào)現(xiàn)實(shí)問(wèn)題的適用性，滿足學(xué)術(shù)研究者和實(shí)踐IT專業(yè)人士的需求，致力于發(fā)表有關(guān)數(shù)據(jù)倉(cāng)庫(kù)和數(shù)據(jù)挖掘的理論發(fā)展和實(shí)際應(yīng)用的高質(zhì)量論文。最初的研究論文、最新的評(píng)論和技術(shù)說(shuō)明被邀請(qǐng)出版。該期刊接受提交與數(shù)據(jù)倉(cāng)庫(kù)和數(shù)據(jù)挖掘相關(guān)的任何工作的論文。特別關(guān)注的是從數(shù)據(jù)倉(cāng)庫(kù)挖掘數(shù)據(jù)的論文；數(shù)據(jù)庫(kù)、數(shù)據(jù)倉(cāng)庫(kù)和數(shù)據(jù)挖掘的集成；以及挖掘和歸檔數(shù)據(jù)的整體方法。主題涵蓋算法應(yīng)用程序問(wèn)題數(shù)據(jù)集市數(shù)據(jù)挖掘數(shù)據(jù)挖掘方法數(shù)據(jù)模型數(shù)據(jù)結(jié)構(gòu)數(shù)據(jù)倉(cāng)庫(kù)數(shù)據(jù)倉(cāng)庫(kù)流程設(shè)計(jì)知識(shí)發(fā)現(xiàn)過(guò)程挖掘數(shù)據(jù)庫(kù)在線分析過(guò)程實(shí)際問(wèn)題工具和語(yǔ)言

投稿網(wǎng)址：http://www.igi-global.com/calls-for-papers/international-journal-data-warehousing-mining/1085

英文簡(jiǎn)介

The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving data.Topics CoveredAlgorithmsApplications issuesData martData MiningData mining methodsData modelsData structuresData WarehousingData warehousing processDesignKnowledge discovery processMining databasesOnline analytical processPractical issuesTools and languages